Quantum computing has emerged as a transformative force in the evolution of computing technology. Recent efforts have applied quantum techniques to classical database challenges, such as query optimization, data integration, index selection, and transaction management. In this paper, we shift focus to a critical yet underexplored area: data management for quantum computing. We are currently in the noisy intermediate-scale quantum (NISQ) era, where qubits, while promising, are fragile and still limited in scale. After differentiating quantum data from classical data, we outline current and future data management paradigms in the NISQ era and beyond. We address the data management challenges arising from the emerging demands of near-term quantum computing. Our goal is to chart a clear course for future quantum-oriented data management research, establishing it as a cornerstone for the advancement of quantum computing in the NISQ era.

Quantum circuit simulation is crucial for quantum computing such as validating quantum algorithms. We present Qymera, a system that repurposes relational database management systems (RDBMSs) for simulation by translating circuits into SQL queries, allowing quantum operations to run natively within an RDBMS. Qymera supports a wide range of quantum circuits, offering a graphical circuit builder and code-based interfaces to input circuits. With a benchmarking framework, Qymera facilitates comparison of RDBMS-based simulation against state-of-the-art simulation methods. Our demonstration showcases Qymera's end-to-end SQL-based execution, seamless integration with classical workflows, and its utility for development, benchmarking, and education in quantum computing and data management. A video demonstrating Qymera's key features can be found at https://youtu.be/j-fTKnVIV6c.